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Spatial Cluster Modelling

List Price: $89.99
SKU:
9780367454913
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  • Product Details

    Author:
    Andrew B. Lawson, David G.T. Denison
    Format:
    Paperback
    Pages:
    308
    Publisher:
    CRC Press (January 29, 2020)
    Language:
    English
    Audience:
    Professional and scholarly
    ISBN-13:
    9780367454913
    Weight:
    19.875oz
    Dimensions:
    6.125" x 9.1875"
    File:
    TAYLORFRANCIS-TayFran_260127073740958-20260127.xml
    Folder:
    TAYLORFRANCIS
    List Price:
    $89.99
    Country of Origin:
    United States
    As low as:
    $85.49
    Publisher Identifier:
    P-CRC
    Discount Code:
    H
    Pub Discount:
    30
    Imprint:
    Chapman and Hall/CRC
    Case Pack:
    1
  • Overview

    Research has generated a number of advances in methods for spatial cluster modelling in recent years, particularly in the area of Bayesian cluster modelling. Along with these advances has come an explosion of interest in the potential applications of this work, especially in epidemiology and genome research.

    In one integrated volume, this book reviews the state-of-the-art in spatial clustering and spatial cluster modelling, bringing together research and applications previously scattered throughout the literature. It begins with an overview of the field, then presents a series of chapters that illuminate the nature and purpose of cluster modelling within different application areas, including astrophysics, epidemiology, ecology, and imaging. The focus then shifts to methods, with discussions on point and object process modelling, perfect sampling of cluster processes, partitioning in space and space-time, spatial and spatio-temporal process modelling, nonparametric methods for clustering, and spatio-temporal cluster modelling.

    Many figures, some in full color, complement the text, and a single section of references cited makes it easy to locate source material. Leading specialists in the field of cluster modelling authored each chapter, and an introduction by the editors to each chapter provides a cohesion not typically found in contributed works. Spatial Cluster Modelling thus offers a singular opportunity to explore this exciting new field, understand its techniques, and apply them in your own research.